Perpetual Innovation

Category: Scenario Planning

  • Scenarios of Stranded Assets in the Oil Patch

    The researchers over at Strategic Business Planning Company have been contemplating scenarios that lead to the demise of oil. The first part of the scenario is beyond obvious. Oil (and coal) are non-renewable resources; they are not sustainable; burning fossil fuels will stop — eventually. It might cease ungracefully, and here are a few driving forces that suggest the cessation of oil could come sooner, not later. Stated differently, if you owned land that is valued based on carbon deposits, or if you owned oil stocks those assets could start to become worth less (or even worthless).

    We won’t spend time on the global warming scenario and possible ramifications of government regulation and/or corporate climate change efforts. These could/would accelerate the change to renewables. There are other drivers away from fossil fuels including: National Security, Moore’s Law toward renewables; and, efficiency.

    1. National Security. Think about all the terrorist groups and rogue countries. All of them get part, or all of their funding from oil (and to a lesser extent, NatGas and Coal). Russia. Iran. Lebanon, where the Russians have been enjoying the trouble they perpetuate. The rogue factions in Nigeria. Venezuela. Even Saudi is not really are best friend (15 of the 19 bombers on 911 were Saudi citizens). Imagine if the world could get off of fossil fuels. Imagine all the money that would be saved, by not having to defend one countries aggression on another if the valuable oil became irrelevant. Imagine how much everyone would save on military. This is more than possible with the current technology; but with Moore’s law of continuous improvement, it becomes even more so.

    2. Moore’s Law. Moore’s law became the law of the land during the computer chip world, where technology is doubling every 18 months, and costs are reducing by half.  (See our blog on The Future of Computing is Taking on a Life of Its Own. After all these decades Moore’s law is finally hitting a wall.) In the renewable world, the price of solar is dropping dramatically, when the efficiency continues to increase. For example the increase of 30% on imported PV, matches the cost reductions of the last year. In the meanwhile battery efficiency is improving dramatically, year-over-year. Entire solar farms have been bid (and built) for about $.02 per kilowatt and wind and/or solar with battery backup is about $.03 per kilowatt. At that price, it is far cheaper to install renewable power vs coal or NatGas, especially given the years to create/develop for fossil fuel plants.

    Note, that we haven’t even talked about peak coal and peak oil. Those concepts are alive and well, just that fracking technology has pushed them back maybe 10 years from a production supply-side perspective. At some point you hit the maximum possible production (on a non-renewable resource) and production can only go down (and prices go up) from there. The world production of oil is now up to 100m barrels per day.  But oil wells deplete at about 4%-5%, so you need 4% more new wells every year. Fracking drops about 25%-30% in the first year! So you need about many more wells each year to stay even. But let’s go on to efficiency and probably the major demand-side force.

    3. Efficiency. The incandescent light bulb, produces very little light… it produces more than 95% heat, and just a tiny bit of light with 100 watts of energy. With only 10-15 watts an LED light can produce the same light was required 100 watts in days of old. The internal combustion engine is hugely inefficient, producing mostly (unused) heat and directly harnessing only 10-15% of energy from gas or diesel… plus it took huge amounts of energy to mine, transport, refine, transport, and retail the fuel. Electric engines are far more efficient, and they produce no toxic emissions. A great book that talks about energy, efficiency and trends is by Ayers & Ayers, Crossing the Energy Divide. The monster power plants (nuclear, coal, NatGas) have serious efficiency issues. They produce huge amounts of heat for steam turbines, but most of the heat is lost/wasted (lets say 50%). Electricity must be transmitted long distances through transmission lines (where up to 40% can be lost in transmission).

    Producing power as needed, where needed, makes so much more sense in most cases. Right now, using today’s technology, pretty much everyone can produce most of their own power (PV or wind) at about the same cost as the power monopolies.  But Moore’s law is making the renewable technology better and better every year. Add some batteries and microgrid technology and you have robust electric systems.

    The losers in these trends/scenarios can be the BIG oil companies and the electric monopolies. They will fight move until they change, or they lose. Just like peak oil, it is a mater of time… but the time is coming faster and faster…

    Saudi is trying to keep prices high enough to complete their oil Initial Public Offering so they can diversify out of oil. Venezuela is offering a new cyber coin IPO (their Petro ICO) with barrels of buried oil as collateral (See Initial Kleptocurrency Offering). But what if that oil becomes a stranded asset? Your Petro currency becomes as worthless as the Venezuelan Bolivar.

    You really want to carefully consider how much and how long you want to own fossil fuel assets… Fossil fuels may be dead in a decade or two… Moore or less.

  • Triangulation to augment your Qual study

    Triangulation in research is a lot the old technology of geometry and surveying where you take the distance from three known points to compute the exact location on a map… Give or take a few yards. LORAN technology using radio signals and such was used in WWII. With a LORAN in the gulf, I remember being able to find where we were on a sail boat, approximately. The problem was that we were in an area of the Gulf of Mexico with only two LORAN readings. Three, you can triangulate, two you can approximate.

    Triangulation in Academic Research is the kind of stuff you can possibly do to augment your Qual study. As discussed other places, Delphi Studies might need to be recharacterized as Mixed method if some of the research is sufficiently quantitative, i.e., if second round has a lot of respondents and it makes sense to do stats, like correlation on several variables.

    So, in any qual study, you might consider including triangulation. There are a few types of triangulation (depending on your source) but let’s focus on just two: data and lit/theoretical. Data would be if you could find published statistics in the area that would allow for some corroboration of the findings from the study. In terms of data, maybe some stats that give an estimate of the independent and/or dependent variables (predictor and predicted variables in QUAL world). Possibly even the intersection of the two. Does the available data align with the findings of the study?

    Internal data to a study should be kept separate from external data triangulation. In Delphi studies, for example, there might be an alignment of the more general findings from round 1 and rankings of round 2. This offers up internal consistency.

    One of the coolest, and potentially strongest, aspects of triangulation is literature (or theory) triangulation. Does the existing literature align with some of the key themes found in your QUAL study. Think of this as a meta-study lite. For a meta study, there needs to be a lot of research, and a deep dive into the existing research can allow for a table of results that support, don’t support, or disprove various themes.

    Here is a very interesting approach for triangulation within a Delphi study (Hopf, Francis, Helms, Haughney, & Bond, 2016). Find the article here at BMJopen. For past studies that did not address a specific topic, they used a bazaar label of “Silence”, as in not addressed in the specific study. A better label would probably not addressed (n.a.). (The implication of silence is that the authors intentionally avoided that specific issue in their study.)

    So, consider including one of the 4 or 5 types of triangulation in your qual study to strengthen the support for your findings (or to highlight divergent findings). For the regular researcher (say dissertation), consider simply doing meta analysis, and avoid all that messy questionnaire stuff, if the field is full of existing research.

    If you use Delphi, you will be able to project into the future. You can explore how some of the themes identified in the research grow or wane in an uncertain future, and what conditions (triggers) might initiate major future disruption, i.e., scenario analysis.

    References

    Hopf, Y. M., Francis, J., Helms, P. J., Haughney, J., & Bond, C. (2016). Core requirements for successful data linkage: an example of a triangulation method. BMJ Open, 6(10), e011879. doi:10.1136/bmjopen-2016-011879 Retrieved from: http://bmjopen.bmj.com/content/6/10/e011879

     

     

  • Scenarios that Jump Out At You

    There are several scenarios that jump out at you.

    Hall and Knab (2012) outlined 11 or so items that were non-sustainable trends/practices that appeared to have compounding and accelerating forces. Those items get worse in a wicked bad way when they go unattended. Therefore, they are wonderful areas to generate scenarios. Here’s a few: US Debt deficit, US Trade deficit, the interest rate bomb, Life-style bomb, the compounding healthcare costs escalation bomb, the fossil fuel energy bust (peak) or bomb (massive government intervention), and the single problem vs integrated problem dilemma.

    There are a few more that jump out in current months. The news and its reliability keeps getting worse. Fake news has become a steady fact. And miss information is well ahead of good, reliable journalism. The SustainZine blog wonders if this is not the time for WikiTribune approach to journalism. There’s many ways that the broken news system can go: from really bad, to even worse; or to use the leverage of computers, networking and crowds to purify it (if only a little). There’s probably no situation where the regular media world of  news, near-news, or fake-news will stay the same as it has evolved in 2016 and 2017.

    Another scenario rich environment is global warming, renewables and fossil fuels. While companies have been steadily getting on-board with the idea that they need to start aiming for sustainable business models, the politics has gotten into a kink. While China and India have made a massive about-face on the Paris conference and actions toward thwarting off Global Warming; the US under Trump is about to go the other way. With the tug-of-war from the deniers and the greenies, it seem likely that something big is about to give. One side will lose and get pulled in, the other side will win, or the rope will snap. If the greenies are right, the world warming will get very bad, very quickly… that’s ugly, but interesting. There will be a lot of oil and gas and coal that will be rendered useless because it can’t be (shouldn’t be) burned. If the deniers are right, the oil, gas and coal companies have many more decades to enjoy unfettered combustion. And Ha Ha to those foolish fear-mongers in Paris.

    Inflation. The US, with $20T in debt on a $19T sized economy based on GDP, currently pays about 9% of all government revenues in interest. (Revenue seems like the wrong word to use for government inflows.) That is at near zero interest rates. When inflation goes up, the fed will end up paying much, even all of the revenues toward servicing the debt. At just over 10% interest, the Fed would pay almost all revenues toward servicing the debt. Nothing for Medicare, SSI, or Military. Oh, and it has been about 8 years, since we have had a good recession, which happens on average every 7 years.

    Gold is an interesting scenario. Lot’s of people thought it would shoot off into space, for many reasons. The US Dollar is strong because it is the best shanty in the slum neighborhood, so gold should look good, relatively.  But maybe a crypto currency like Bitcoin, massive federal government interventions around the world –and other factors — have taken the luster off of what some consider the most secure investment in the world?

    What other scenarios do you see looming?

    What’s the best way for a business to prepare for some of these scenarios that loom large?

    References

    Hall, E., & Knab, E.F. (2012, July). Social irresponsibility provides opportunity for the win-win-win of Sustainable Leadership. In C. A. Lentz (Ed.), The Refractive Thinker: Vol. 7. Social responsibility (pp. 197-220). Las Vegas, NV: The Lentz Leadership Institute.
    (Available from www.RefractiveThinker.com, ISBN: 978-0-9840054-2-0)

  • Intel and Mobile Computing: An Eye on BIG Computing on the Move

    We are rapidly moving to one of the most disruptive innovations in modern computing. Truly mobile computing. The Driver-less car. These cars are going to have a lot of computing power on-board. They will need to be self contained, after all, if going through a tunnel or parking lot. But they will be amassing massive amounts of data as well, 4 terabytes of data per day for the average self-driving car. Wow. And current mobile data plans start to charge you or throttle you after about 10MB of data usage per month.

    Read about this in a great WSJ article by Greenwald on March 13. It focuses on the companies in play and the new bid by Intel to buy MobilEye for $15.3B, the look-around and self driving technology going into GM, VW & Honda cars. The 34% premium shows how important this tech is to the slumbering Tel Giant.

    What’s all the fuss about driver-less cars? How does going Driver-Less impact the future: what are potential interruptions, problems and/or discontinuities? How could this technology alter the strategic plans for many market leaders?

    It seems likely that the majority of Americans will reject using/supporting driver-less vehicles… for a while.  It removes individual control, emasculates the sense of manly power while removing decision making.  One cannot demonstrate a charged-up ego to a potential partner when a computer and sensors are driving the speed limit behind a school bus.  A driver can suddenly opt for a shortcut or a scenic route that he knows by heart.  Not so the driver-less vehicle. However, Tesla drivers have already been reprimanded, for letting the car do too much of the driving, under too many unusual circumstances.

    Just a few things to think further about: Long-Haul Trucking and Enabling Technologies.

    Long-haul trucking. There is a major shortage of truck drivers. Labor rules don’t let drivers do long hauls without breaks or rest. So long haul driving often uses two drivers for the same truck that is going coast to coast. If the truck needs to stop and drop along the way, however, then a person on-board, might still be necessary. However drops and pickups usually have someone there at the warehouse who can assist. How will the truck fuel itself up at the Flying-J truck stops? If we can fuel up fighter jets in mid air, we can figure out how to fuel up a driver-less truck. One obvious solutions – or not so obvious, if you’re not in the habit of longer-term and sustainable thinking – is to move to electric trucks and a charging pad. Simply drive the electric truck over a rapid-charging pad. Rapid-charge technology is already generally available using current technologies (especially with minor improvements in batteries and charging).

    Enabling Technology Units (ETUs).  The MobilEye-types of technology apply to lots and lots of other situations, such as trucks, farm tractors, forklifts, etc. Much of the technology being developed for the driver-less car is what Hall & Hinkelman (2013) refer to as Enabling Technology Units (ETUs) in their Guide book to Patent Commercialization. The base technologies have many and broad based applications beyond the obvious direct market application. It is the Internet of things, when the “things” are mobile, or when the “things” around it are mobile, or both. This is an interesting future of mobile computing.

    References

    Hall, E. B. & Hinkelman, R. M. (2013). Perpetual Innovation™: A guide to strategic planning, patent commercialization and enduring competitive advantage, Version 2.0. Morrisville, NC: LuLu Press. ISBN: 978-1-304-11687-1  Retrieved from: http://www.lulu.com/spotlight/SBPlan

  • Scenarios Now and the Genius (hidden) within Crowd

    It’s been about 10 years since the Great Recession of 2007-2008. (It formally started in December of 2007.) A 2009 McKinsey study showed that CEOs wished that they had done more scenario planning that would have made them more flexible and resilient through the great recession. In a 2011 article, Hall (2011) discusses the genius of crowds and group planning – especially scenario planning.

    The Hall article spent a lot of time assessing group collaboration, especially utilizing the power available via the Internet. Wikipedia is one of the greatest collaboration – and most successful – tools of all time. It is a non-profit that invokes millions of volunteers daily to add content and regulate the quality of the facts. In this day of faus news, Wikipedia is a stable island in the turbulent ocean of content. Anyone who has corrections to make to any page (called article) is encouraged to do so. However, the corrections need to fact-based and source rich. Unlike a typical wiki, where anything goes, the quality of content is very tightly controlled.  As new information and research comes out on a topic, Wikipedia articles usually reflect those changes quickly and accurately. Bogus information usually doesn’t make it in, and bias writing is usually flagged. Sources are requested when an unsubstantiated fact is presented.

    Okay, that’s one of the best ways to use crowds. People with an active interest – and maybe even a high level of expertise – update the content. But what happens when the crowd is a group of laypeople. Jay Leno made an entire career from the “wisdom” of people on the street when he was out Jay Walking. The lack of general knowledge in many areas is staggering.  Info about the latest scandal or gossip by celebs, on the other hand, might be really well circulated. So how can you gather information from a crowd of people where the crowd may be generally wrong?

    It turns out that researchers at MIT and Princeton have figured out how to use statistics to figure out when the crowd is right and when the informed minority is much more accurate (Prelec, Seung & McCoy, 2017).  (See a Daniel Akst overview WSJ article here.) Let’s say you are asking a lot of people a question in which the general crowd is misinformed. The answer, on average, will be wrong. There might be a select few in the crowd who really do know the answer, but their voices are downed out, statistically speaking. These researchers took a very clever approach; they ask a follow-on question about what everyone else will answer. The people who really know will often have a very accurate idea of how wrong the crowd will be. So the questions with big disparities can be identified and you can give credit to the informed few while ignoring the loud noise from the crowd.

    Very cool. That’s how you can squeeze out knowledge and wisdom from a noisy crowd of less-than-informed people.

    The question begs to be asked, however: Why not simply ask the respondents how certain they are? Or, maybe, ask the people of Pennsylvania what their state capital is, not the other 49 states who will generally get it wrong. Maybe even put some money on it to add a little incentive for true positives combined with costly incorrect answers such that only the crazy or the informed will “bet the farm” on answers where they are not absolutely positive?

    But then, that too is another study.

    Now, to return to scenario planning. Usually with scenario planning, you would have people that are already well informed. However, broad problems have different silos of expertise. Maybe a degree of comfort or confidence would be possible in the process of scenario creation. Areas where a specific participant feels more confident might get more weight than other areas where their confidence is lower. Hmm… Sounds like something that could be done very well with Delphi, provided there were well informed people to poll.

    Note scenarios are different from probabilities… Often scenarios are not high probabilities… You are usually looking at possible scenarios that are viable… The “base case” scenario is what goes into the business plan so that may be the 50% scenario; but all the other scenarios are everything else. The base case is only really likely to occur if nothing major changes in the macro and the micro economic world. Changes always happen, but the question is, does the change “signal” that the bus has left the freeway, and now new scenario(s) are at play.

    The average recession occurs every 7 years into a recovery. We are about 10 years into recovery from the Great Recession. Of course, many of the Trump factors could be massively disrupting. Not to name them all, but on the most positive case, a 4% to 5% economic growth in the USA, should be a scenario that every business should be considering. (A strengthening US and world economy may, or may not, be directly caused by Trump.) The nice thing about having sound scenario planning, as new “triggers” arise, they may (should) lead directly into existing scenarios.

    Having no scenario planning in your business plan… now that seems like a very bad plan.

    Reference

    Hall, E. (2009). The Delphi primer: Doing real-world or academic research using a mixed-method approach. In C. A. Lentz (Ed.), The refractive thinker: Vol. 2. Research methodology (2nd ed., pp. 3-28). Las Vegas, NV: The Lentz Leadership Institute. (www.RefractiveThinker.com)

    Hall, E. (2010). Innovation out of turbulence: Scenario and survival plans that utilizes groups and the wisdom of crowds. In C. A. Lentz (Ed.), The refractive thinker: Vol. 5. Strategy in innovation (5th ed., pp. 1-30). Las Vegas, NV: The Lentz Leadership Institute. (www.RefractiveThinker.com)

    Prelec, D., Seung, H. S., & McCoy, J. (2017, January 26). A solution to the single-question crowd wisdom problem. Nature. 541(7638), 532-535. 10.1038/nature21054 Retrieved from: http://www.nature.com/nature/journal/v541/n7638/full/nature21054.html